System and method for molecular breast imaging

ABSTRACT

A method for motion correcting molecular breast imaging (MBI) images includes obtaining a plurality of two-dimensional (2D) images of a breast using a MBI system, selecting a reference image from the plurality of 2D images, selecting a feature of interest in the reference image, determining a location of the feature of interest in the reference image, calculating a correction value based on a difference in the location of the feature of interest in the reference image and a location of the feature of interest in a plurality of non-reference images, and aligning the non-reference 2D images with the reference image based on the calculated correction value.

BACKGROUND OF THE INVENTION

The subject matter disclosed herein relates generally to systems andmethods for diagnostic medical imaging, and more particularly toMolecular Breast Imaging (MBI) systems.

Molecular Breast Imaging (MBI) is used to image breasts to detect, forexample, tumors, lesions, and/or cancer. In operation, a patient ispositioned within the MBI system such that the patient's breast ispositioned between a pair of detectors. A single or a plurality oftwo-dimensional (2D) images, commonly each at a different orientation inrespect to the patient's breast, is then acquired.

In operation, patient organ and lesion motion may be a significantsource of image quality degradation. Respiratory motion is the mostcommon involuntary motion encountered in MBI imaging due to the requiredduration of MBI scanning necessary to obtain clinically usefulinformation. More specifically, in some cases the patient may moveinvoluntarily such that the position of the breast is not consistentduring the acquisition of each of the images. For example, in contrastto mammography imaging, where the breast is compressed for a shortduration it takes to complete the X-ray exposure, MBI imaging generallyperforms data acquisition for several minutes. In some cases, a patientmay experience discomfort due to the duration of the MBI imaging scan.Therefore, for MBI imaging the breast is immobilized between the MBIdetectors using reduced pressure in comparison to the pressure used inmammography imaging. The reduced pressure is less effective in holdingthe breast in a fixed position and may therefore allow some motion ofthe breast respective to the MBI detectors. The combination of thereduced pressure and long imaging time may therefore increase thelikelihood of image blurring due to motion. The involuntary motion maybe particularly detrimental when a physician is determining the size ofa lesion, determining the location of the lesion, or quantifying thelesion.

BRIEF DESCRIPTION OF THE INVENTION

In accordance with various embodiments, a method for motion correctingmolecular breast imaging (MBI) images is provided. The method includesobtaining a plurality of two-dimensional (2D) images of a breast using aMBI system, selecting a reference image from the plurality of 2D images,selecting a feature of interest in the reference image, determining alocation of the feature of interest in the reference image, calculatinga correction value based on a difference in the location of the featureof interest in the reference image and a location of the feature ofinterest in a plurality of non-reference images, and aligning thenon-reference images with the reference image based on the calculatedcorrection value.

In accordance with other various embodiments, a molecular breast imaging(MBI) system is provided. The MBI system includes at least one detectorhaving a plurality of pixels and a processing unit coupled to thedetector. The processing unit is configured to obtain a plurality oftwo-dimensional (2D) images of a breast using a MBI system, receive auser input selecting a reference image from the plurality of 2D images,receive a user input selecting a feature of interest in the referenceimage, determine a location of the feature of interest in the referenceimage, calculate a correction value for each of a plurality ofnon-reference images based on a difference in a location of the featureof interest in the reference image and a location of the feature ofinterest in each of the non-reference images, and combine thenon-reference images with the reference image based on the calculatedcorrection values.

In a further embodiment, a non-transitory computer readable medium isprovided. The non-transitory computer readable medium is encoded with aprogram to instruct a processing unit to obtain a plurality oftwo-dimensional (2D) images of a breast using a MBI system, receive auser input selecting a reference image from the plurality of 2D images,receive a user input selecting a feature of interest in the referenceimage, determine a location of the feature of interest in the referenceimage, calculate a correction value for each of a plurality ofnon-reference images based on a difference in a location of the featureof interest in the reference image and a location of the feature ofinterest in each of the non-reference 2D images, and combine thenon-reference images with the reference image based on the calculatedcorrection values.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 a block diagram of an exemplary nuclear medicine imaging systemembodied as a Molecular Breast Imaging (MBI) system constructed inaccordance with various embodiments.

FIG. 2 is a method of detecting and correcting motion affected images inaccordance with various embodiments.

FIG. 3 is a simplified block diagram of a plurality of images that maybe generated in accordance with various embodiments.

FIG. 4 is a two-dimensional image that may be generated in accordancewith various embodiments.

FIGS. 5A and 5B are two-dimensional images that may be generated inaccordance with various embodiments.

FIGS. 6A-6D are graphical illustrations of exemplary correction valuesthat may be generated in accordance with various embodiments.

DETAILED DESCRIPTION OF THE INVENTION

The foregoing summary, as well as the following detailed description ofcertain embodiments of the present invention, will be better understoodwhen read in conjunction with the appended drawings. To the extent thatthe figures illustrate diagrams of the functional blocks of variousembodiments, the functional blocks are not necessarily indicative of thedivision between hardware circuitry. For example, one or more of thefunctional blocks (e.g., processors or memories) may be implemented in asingle piece of hardware (e.g., a general purpose signal processor or ablock of random access memory, hard disk, or the like) or multiplepieces of hardware. Similarly, the programs may be stand alone programs,may be incorporated as subroutines in an operating system, may befunctions in an installed software package, and the like. It should beunderstood that the various embodiments are not limited to thearrangements and instrumentality shown in the drawings.

As used herein, an element or step recited in the singular and proceededwith the word “a” or “an” should be understood as not excluding pluralof said elements or steps, unless such exclusion is explicitly stated.Furthermore, references to “one embodiment” of the present invention arenot intended to be interpreted as excluding the existence of additionalembodiments that also incorporate the recited features. Moreover, unlessexplicitly stated to the contrary, embodiments “comprising” or “having”an element or a plurality of elements having a particular property mayinclude additional elements not having that property.

Various embodiments provide a method for motion correcting imagesacquired using a Nuclear Medicine (NM) imaging system. For example,various embodiments provide a Molecular Breast Imaging (MBI) system anda method to acquire temporal imaging data of a patient's breast.Temporal as used herein means that the imaging data is time stamped suchthat a location of an event detected by the detectors may be associatedwith a time when the event was detected by the detectors. The temporalimaging data may be acquired in real-time while the MBI system isperforming a dynamic scan of the breast. Optionally, the temporalemission data may be acquired after the breast is scanned. For example,the temporal emission data may be stored as list mode data. The temporalemission data may then be utilized to detect patterns in the images andalso track variations of the movement over time. More specifically, themovement of a feature of interest may be measured to generate acorrection value that is applied to the various images and/or list modedata acquired using the MBI system.

In various embodiments, the methods described herein may be implementedusing an exemplary MBI system 10 shown in FIG. 1. The MBI system 10includes imaging detectors 12 and 14 mounted on or to a gantry 16. Eachdetector 12 and 14 generally captures a two-dimensional (2D) image thatmay be defined by the x and y location of the pixel and the detectornumber. Moreover, in various embodiments, the 2D image captured by thedetector 12 is obtained from a view that is approximately 180 degreesaway from the 2D image captured by the detector 14. Further, in otherexemplary embodiments, at least one of the detectors 12 and 14 maychange orientation relative to the stationary or movable gantry 16. Thedetectors 12 and 14 may be registered such that features appearing at agiven location in one detector may be correctly located and the datacorrelated in the other detector. Accordingly, in various embodimentscommon features in the two images acquired by the imaging detectors 12and 14 may be combined.

Each of the detectors 12 and 14 has a radiation detection face (notshown) that is directed towards a structure of interest, for example, abreast 20 there between that may have a lesion. A pair of collimators 22and 24 may be provided in combination or connection with the detectors12 and 14, respectively. In various embodiments, the radiation detectionfaces of the detectors 12 and 14 are covered by the collimators 22 and24. In some embodiments, the collimators 22 and 24 are registeredparallel holes collimators coupled to the detection faces of thedetectors 12 and 14.

For example, the detectors 12 and 14 may include collimators 22 and 24,respectively, provided directly on the surface of the detectors 12 and14 and illustrated as parallel hole collimators. The detectors 12 and 14are also capable of being rotated to some angle to provide variousimages of the breast 20 while remaining substantially parallel to eachother. More specifically, the detector pair 12 and 1 generally remain ina parallel configuration, and the detector pair is tilted in unison toobtain different views of the breast. In all, each breast is generallyimaged at least twice (two views per breast).

Additionally, the distance between the two detectors 12 and 14 may bechanged to accommodate breasts with different sizes and to immobilizethe breast for the duration of data acquisition, which may includeapplying light pressure to the breast. The distance between near facesof the two collimators 22 and 24 is registered automatically ormanually. Although illustrated as a parallel hole collimators 22 and 24,different types of collimators as known in the art may be used, such aspinhole, fan-beam, cone-beam, diverging type collimators, and/ormulti-bore per pixel collimators. An actual field of view (FOV) of eachof the detectors 12 and 14 may be directly proportional to the size andshape of the respective imaging detector, or may be changed usingcollimation. In various embodiments, the detectors 12 and 14 may beformed of cadmium zinc telluride (CZT) tiles or alternatively anytwo-dimensional pixelated detector.

The MBI system 10 may also includes a motion controller unit 30 tocontrol the movement and positioning of the gantry 16 and/or thedetectors 12 and 14 with respect to each other to position the breast 20within the FOVs of the imaging detectors 12 and 14 prior to acquiring animage of the breast 20. Optionally, the MBI system 10 may be operatedmanually by the user to reposition the detectors 12 and 14. Moreover,pressure sensors (not shown) may be used to assist the user inpreventing from applying excessive force on the breast while positioningthe breast between the detectors 12 and 14. The controller unit 30includes a detector controller 32 and a gantry motor controller 34 thatmay be automatically commanded by a processing unit 36, manuallycontrolled by an operator, or a combination thereof. The gantry motorcontroller 34 and the detector controller 32 may move the detectors 12and 14 with respect to the breast 20 individually, in segments orsimultaneously in a fixed relationship to one another. Alternatively,one or more collimators 22 and 24 may be moved relative to the detectors12 and 14. The distance between the detectors 12 and 14 may beregistered by the controller unit 30 and used by the processing unit 36during data processing. In some embodiments, motion is manually detectedby the operator and the controller unit 30 is replaced with scales orencoders for measuring the distance between the detectors 12 and 14, thedetector orientation, and/or any immobilization force exerted by atleast one detector 12 and/or 14 on the breast 20.

During operation, the breast 20 is positioned between the detectors 12and 14 and at least one of the detectors 12 and/or 14 is translated toimmobilize the breast 20 between the detectors 12 and 14. The detectors12 and 14 are then used to acquire temporal image data of the breast 20,which may include one or more lesions, for example a breast cancertumor, within the breast 20. The detectors 12 and 14 and the gantry 16generally remain stationary after being initially positioned, and thetemporal imaging data is acquired. The temporal imaging data may then becombined into a composite image that includes a plurality oftwo-dimensional (2D) images 46, wherein each 2D image 46 is acquired ata different point in time during the scan.

The MBI system 10 also includes a Data Acquisition System (DAS) 40 thatreceives analog and/or digital electrical signal data produced by thedetectors 12 and 14 and decodes the data for subsequent processing inthe processing unit 36. A data storage device 42 may be provided tostore data from the DAS 40 or other types of data. For example, the datastorage device 42 may store emission data 44 acquired from the detectors12 and 14 during a scan of the breast 20. In various embodiments, theemission data 44 may be utilized generate a plurality of 2D images orframes 46 of the breast 20. Optionally, the emission data 44 may bestored as list mode data 48 of the breast 20 acquired during a previousscan, e.g. event-by-event data acquisition. In a “list-mode”acquisition, each detected photon is associated with: x, y, detector 12or 14, and a “time stamp”. The “time stamp” is the absolute time of theevent, or time since the beginning of the acquisition. An input device50 (e.g., user console with keyboard, mouse, etc.) also may be providedto receive user inputs and a display 52 may be provided to displayimages.

In various embodiments, the MBI system 10 also includes a motiondetection and correction module 60 that is configured to implementvarious methods described herein. The module 60 may be implemented as apiece of hardware that is installed in, for example, the processing unit36. Optionally, the module 60 may be implemented as a set ofinstructions that are installed on the processing unit 36. The set ofinstructions may be stand alone programs, may be incorporated assubroutines in an operating system installed on the processing unit 36,may be functions in an installed software package on the processing unit36, and the like. It should be understood that the various embodimentsare not limited to the arrangements and instrumentality shown in thedrawings. For example, in some embodiments, the MBI system 10 mayinclude a “viewing station” (not shown) that is used by the physician toevaluate the images. Thus, the motion detection and correction module 60may be located at the “viewing station” which may be located remotelyfrom the MBI system 10.

The set of instructions may include various commands that instruct themodule 60 and/or the processing unit 36 as a processing machine toperform specific operations such as the methods and processes of thevarious embodiments described herein. The set of instructions may be inthe form of a non-transitory computer readable medium. As used herein,the terms “software” and “firmware” are interchangeable, and include anycomputer program stored in memory for execution by a computer, includingRAM memory, ROM memory, EPROM memory, EEPROM memory, and non-volatileRAM (NVRAM) memory. The above memory types are exemplary only, and arethus not limiting as to the types of memory usable for storage of acomputer program.

FIG. 2 is a simplified block diagram of an exemplary method 100 that maybe utilized to perform motion detection and correction of the images 46and/or list mode data 48 described above. In various embodiments, themethod 100 may be utilized to either automatically or manually select aportion of the breast 20 in a first or reference image in the set of 2Dimages 46 and then to register or align the non-reference images 46 withthe reference image based on the selected portion. As used herein, theterm “non-reference images” refers to each of the 2D images that are notdesignated as the reference image. Assuming that a set N of 2D images isgenerated, and a single referenced image is selected from the set of N2D images. The non-reference 2D images form a set having N-1 images,e.g. the non-reference images. In the exemplary embodiment, the method100 may be implemented using the processing unit 36 and/or the motiondetection and correction module 60 (shown in FIG. 1). The method 100 maytherefore be provided as a non-transitory computer-readable medium ormedia having instructions recorded thereon for directing the processingunit 36 and/or the motion detection and correction module 60 to performan embodiment of the methods described herein. The medium or media maybe any type of CD-ROM, DVD, floppy disk, hard disk, optical disk, flashRAM drive, or other type of computer-readable medium or a combinationthereof.

Referring to FIG. 2, at 102 the patient's breast 20 is scanned togenerate an emission dataset, such as the emission dataset 44 (shown inFIG. 1). In the exemplary embodiment, the emission dataset 44 may beacquired using the MBI system 10 (shown in FIG. 1). For example, theemission dataset 44 may be acquired by performing a scan of the breast20 to produce the emission dataset 44. Optionally, the emission dataset44 may be acquired from data collected during a previous scan of thebreast 20, wherein the emission dataset 44 has been stored in a memory,such as the data storage device 42 (shown in FIG. 1). The emissiondataset 44 may be stored in any format, such as a plurality of 2D images46 or a list mode dataset 48, for example. The emission dataset 44 maybe acquired during real-time scanning of the breast 20. For example, themethods described herein may be performed on emission data as theemission dataset 44 is received from the MBI system 10 during areal-time examination of the breast 20.

At 104, a plurality of 2D images, such as the 2D images 46 are generatedusing the emission dataset 44 acquired at 102. More specifically, and asshown in FIG. 3, assume that at 102 a length of the scan of the breast20 is ten minutes. Moreover, assume that an operator desires to generatea 2D image using emission data acquired over a 1 minute period.Accordingly, in the exemplary embodiment, shown in FIG. 3, ten 2D imageslabeled 46 a . . . 46 n are generated. It should be realized that thebreast 20 may be scanned for any length of desired time, and ten minutesis one such exemplary scan time. Moreover, it should be realized that asingle 2D image may be generated using emission data acquired over anylength of time. For example, assume again that the breast 20 is scannedfor five minutes. Moreover, assume that each 2D image is generated usingemission data acquired over a thirty second time period. In thisexample, fifteen 2D images 46 are generated at 104.

Referring again to FIG. 2, method 100 further includes selecting at 106a reference image 150 from the plurality of 2D images 46, for example,selecting the 2D image 46 a shown in FIG. 3, as the reference image 150shown in FIG. 4. In operation, the reference image 150 is used as abaseline image for aligning each of the non-reference images 46 b . . .46 n with the reference image 150. More specifically, and as describedin more detail below, the location or coordinates of a feature ofinterest in the reference image 150 are initially determined. Thelocation or coordinates of the same feature of interest are thendetermined in each of the non-reference images 46 b . . . 46 n. Thecoordinates of the feature of interest in the non-reference images 46 b. . . 46 n may then be shifted, using a correction value, such that thefeature of interest in the non-reference images 46 b . . . 46 n is atthe same coordinates as the feature of interest in the reference image150. More specifically, the non-reference images 46 b . . . 46 n areregistered with respect to the reference image 150 based on thecorrection value, as described in more detail below. Accordingly, whenthe reference image 150 is combined with the non-reference images 46 b .. . 46 n to form a final 2D image, the feature of interest selected bythe user is aligned in each of the 2D images such that the final 2Dimage has reduced blurring, etc. In various embodiments, any of the 2Dimages may be selected as the reference image 150. In the illustratedembodiment, the first 2D image 46 a acquired during the scan of thebreast 20 is selected as the reference image 150. However, it should berealized that any of the non-reference images 46 b . . . 6 n acquiredduring the scan of the breast 20 may be selected as the reference image150.

Referring again to FIG. 2, at 108 a feature of interest 152 in thereference image 150 is selected. In various embodiments, the feature ofinterest 152 may be a tumor, lesion, or other physical feature 154within the breast 20. In other embodiments, the feature of interest 152may be an edge, surface or wall 156 of the breast 20. In operation, thefeature of interest 152 selected in the reference image 150 is utilizedto register or align the non-reference images 46 a . . . 46 n with thereference image 150, e.g. the 2D image 46 a. For example, assume thatupon reviewing the reference image 150, the user determines that twolesions are shown. The user may determine that a first lesion is ofclinical importance while the second lesion is not of clinicalimportance. The two lesions may appear at first locations in thereference image 150 and at different locations in the non-referenceimages 46 b . . . 46 n as the patient moves. The user may select, usingthe input device 50 for example the first lesion as the feature ofinterest 152 such that when the non-reference images 46 b . . . 46 n arecombined with the reference image 150, the feature of interest 152 isaligned in each of the images, and the resultant or final 2D image showsthe feature of interest 152 having reduced blurring, etc, to enable theuser to measure or otherwise quantify the lesion more accurately.

At 110 a correction value is calculated for each of the non-referenceimages 46 b . . . 46 n based on a difference in a location of thefeature of interest 152 in the reference image 150 and a location of thefeature of interest 152 in the non-reference images 46 b . . . 46 n. Forexample, the correction value may represent a set of X-Y coordinatesthat are used to align the feature of interest 152 in the non-referenceimages 46 b . . . 46 n with the feature of interest 152 in the referenceimage 150. More specifically, the correction value may be a set of X-Ycoordinates that represent a difference between the position of thefeature of interest 152 in the non-reference images 46 b . . . 46 n andthe position of the feature of interest 152 in the reference image 150.The correction value may also represent a vector having a direction anda magnitude, wherein the direction indicates the direction along theX-axis and/or the Y axis the feature of interest 152 in thenon-reference images 46 b . . . 46 n should be moved to align thefeature of interest 152 in the non-reference images 46 b . . . 46 n withthe feature of interest 152 in the reference image 150. The magnitude ofthe vector represents a quantity of movement in the along the X-axisand/or the Y axis to move the feature of interest 152 in thenon-reference images 46 b . . . 46 n to align the feature of interest152 in the non-reference images 46 b . . . 46 n with the feature ofinterest 152 in the reference image 150. The correction value isdetermined for each of the non-reference images 46 b . . . 46 n. Invarious embodiments, to generate the correction value at 110, a boundaryof the feature of interest 152 in the reference image 150 is determinedat 112. Moreover, at 114 the boundary of the feature of interest 152 inthe non-reference images 46 b . . . 46 n is determined.

For example, FIG. 5A shows the reference image 150 wherein the lesion154 is positioned at a first location. Moreover, FIG. 5B shows the 2Dimage 46 b wherein the lesion 154 is positioned at a second location dueto patient movement between the acquisition of the reference image 150and the acquisition of the 2D image 46 b. In various embodiments, at 112a boundary 160 is calculated for the lesion 154 in the reference image150 and at 114 a second boundary 162 is calculated for the lesion 154shown in the 2D image 46 b. It should be realized that the boundary 160is substantially similar to the boundary 162, e.g. has the same size andshape. However, because the location of the lesion 154 in the referenceimage 150 is different than the location of the lesion 154 in the image46 b, due to patient motion, the location of the boundary 160 in thereference image 150 is different than the location of the boundary 162in the image 46 b. For example, as shown in FIG. 5A, assume that acenter 190 of the lesion 154 is located at X,Y coordinates (0,0).Moreover, assume that the center 190 of the lesion 154 as shifted inFIG. 5B to X, Y coordinates (0,1). Thus, in the exemplary embodiment,the lesion 154 is the same in the X direction in both the referenceimage 150 and the image 46 b. However, because of motion, the lesion 154has shifted in the Y direction. Accordingly, the correction valuecalculated for the image 46 b may be for example, (0,−1) to instruct theprocessing unit 36 to shift the image 46 b by one pixel in the Ydirection such that lesion 154 in image 46 b is aligned with the lesion154 in the reference image 150. Accordingly, when the image 46 b iscombined with the reference image 150, the feature of interest 152, e.g.the lesion 154 is aligned in all of the images. Similarly, a boundary iscalculated for the other non-reference images 46 c . . . 46 n to alignthe lesion 154 in the images 46 c . . . 46 n with the lesion 154 in thereference image.

In various embodiments, the boundaries 160 and 162 may be calculated bya user manually drawing or virtually tracing on a screen the boundaries160 and 162, respectively, that enclose the lesion 154 as shown in FIGS.5A and 5B. The boundaries 160 and 162 may be drawn around the lesion 154using the input device 50, for example. In other embodiments, theboundaries 160 and 162 may be calculated semi-automatically, wherein auser defines a center point within the lesion 154 and the processingunit 36 then defines the boundaries 160 and 162 based on the definedcenter point. For example, when the boundaries 160 and 162 arecalculated semi-automatically, the user may position a center point 180and a center point 182 on the lesion 154 in both the reference image 150and the non-reference images 46 b . . . 46 n, the processing unit 36 maythen automatically calculate the boundaries 160 and 162. The boundaries160 and 162 may also be generated automatically using the processingunit 36 and/or the motion detection and correction module 60. Forexample, the processing unit 36 may determine a pixel intensity vale foreach pixel in the reference image 150 and the non-reference images 46 b. . . 46 n. The processing unit 36 may then compare the pixel intensityvalues to known pixel intensity values of, for example, a known lesion.Based on the comparison, the processing unit 36 may automaticallyidentify the lesion 154 and automatically draw a boundary around thelesion 154 as described above.

More specifically, the processing unit 36 generates the boundaries 160and 162 using a principle, whereby it is generally assumed that variousorgans, tissue, fluid, and other anatomical features, surrounding thelesion 154 may be differentiated from the lesion 154 by determining anintensity value for each pixel in the reference image 150 and the 2Dimage 46 b. Based on the intensity values of each of the pixels, thelesion 154 may be distinguished from the other anatomical features.Accordingly, the boundary 160 is calculated by automatically comparingthe intensity value for each pixel in the reference image 160 to apredetermined intensity value, using for example, a thresholding processto identify the lesion 154 and generate the boundary 160 around thelesion 154. Automatic determination of the lesion may be done forexample by calculating the average “non-air” intensity. The thresholdmay then be set to a predefined percentage (e.g. 20% or 50% aboveaverage). Optionally, a “histogram” of pixel values may be plotted,wherein the lowest (˜“0”) peak is air, the main peak=“normal tissue”,and the higher peak(s)=lesion(s). The threshold may be set at “valley”above the main peak. Similarly, the boundary 162 is calculated byautomatically comparing the intensity value for each pixel in the 2Dimage 46 b to a predetermined intensity value, using for example, athresholding process to identify the lesion 154 and generate theboundary 162 around the lesion 154 in the 2D image 46 b.

Similarly, the processing unit 36 may generates boundaries around thesurface of the breast 20. For example, and referring again to FIGS. 5Aand 5B, the processing unit 36 may generate a boundary 170 around aportion of the breast 20 in the reference image 150. Moreover, theprocessing unit 36 may generate a boundary 172 around a portion of thebreast 20 of the 2D image 46 b as shown in FIG. 5B. In variousembodiments, the boundaries 170 and 172 are determined or calculatedsimilar to the boundaries 160 and 162 described above. For example, andas described above it is generally assumed that breast tissue and theother physical features within the breast 20, such as for example thelesion 154, may be differentiated from the area surrounding the breast20 which is air. Therefore intensity values of the pixels representingthe breast 20 are different than the intensity values of the pixelssurrounding the breast 20. Based on the intensity values of each of thepixels, the breast 20 may be distinguished from air surrounding thebreast 20. Accordingly, the boundaries 170 and 172 are calculated byautomatically comparing the intensity value for each pixel in thereference image 160 to a predetermined intensity value, using forexample, a thresholding process to identify boundaries 170 and 172,respectively between the breast 20 and the air.

More specifically, to generate the boundaries 170 and 172, the methodautomatically compares the intensity value for each pixel in thereference image 150 to a predetermined intensity value, using forexample, a thresholding process. In the exemplary embodiment, thepredetermined intensity value may be a range of predetermined intensityvalues. The predetermined value range may be automatically set based ona priori information of the breast 20. Optionally, the predeterminedrange may be manually input by the operator. In one embodiment, if theintensity value of a pixel is within the predetermined range, the pixelis classified as belonging to the breast 20. Otherwise, the pixel isclassified as not belonging to the air. It should be realized that othermethods may be utilized to calculate the boundaries 170 and 172 of thebreast 20.

Optionally, the processing unit 36 may determine the correction valuesbased on the center points 180 themselves. For example, the processingunit 36 may compare the location of the center point 180 to each of thecenter points 182 in the non-reference images 46 b . . . 46 n togenerate a plurality of correction values, wherein each correction valuerepresents a difference in the location of the center point 180 and thecenter points 182 in the non-reference images 46 b . . . 46 n.

Accordingly, at 110 the correction value, in some embodiments, iscalculated by determining a difference in a location, e.g. the boundary160, of the feature of interest 152 in the reference image 150 and alocation, e.g. the boundary 162, of the feature of interest 152 in thenon-reference images 46 b . . . 46 n. Optionally, the correction valueis generated using the center points 180 and 182 described above. Morespecifically, at the X-Y coordinates of the boundary 162 are compared tothe baseline X-Y coordinates of the boundary 160 in the reference image150 to calculate a difference in the location of the boundary 160 in thereference image 150 and each of the boundaries 162 calculated in thenon-reference images 46 b . . . 46 n. The difference in the X-Ycoordinates of the boundary 160 and the X-Y coordinates of theboundaries 162 in each of the non-reference images 46 b . . . 46 n arereferred to herein as the correction values. It should be appreciatedthat a correction value is calculated for each of the non-referenceimages 46 a . . . 46 n to enable each of the non-reference images 46 b .. . 46 n to be aligned with the reference image 150.

For example, FIGS. 6A-6D are a plurality of graphical illustrationsshowing exemplary the movement of the breast 20 during the imageacquisition process and a plurality of correction values that may begenerated using the various methods and systems described herein. InFIGS. 6A-6D, the x-axis represents the image number and the y-axisrepresents the location of the feature of interest 152. As shown in FIG.6A, the left side of the graph shows the horizontal position of thefeature of interest 152 in the reference image 150 denoted at position0. Positions 1-9 on the x-axis show the horizontal position of thefeature of interest 152 in the non-reference images 46 b . . . 46 n.Additionally, as shown in FIG. 6B, the left side of the graph shows thevertical position of the feature of interest 152 in the reference image150 denoted at position 0. Positions 1-9 on the x axis show the verticalhorizontal position of the feature of interest 152 in the non-referenceimages 46 b . . . 46 n.

FIG. 6C illustrates the positions 0-8 on the x-axis show the horizontalposition of the feature of interest 152 after the correction is appliedto align each of the non-reference images 46 b . . . 46 n to thereference image 150 in the horizontal direction. Additionally, FIG. 6Dillustrates the positions 0-8 on the x-axis show the vertical positionof the feature of interest 152 after the correction is applied to aligneach of the non-reference images 46 b . . . 46 n to the reference image150 in the vertical direction. Accordingly, each of the points 200 . . .200 n represent correction values applied to each of the non-referenceimages 46 b . . . 46 n in the horizontal direction and each of thepoints 210 . . . 210 n represent correction values applied to each ofthe non-reference images 46 b . . . 46 n in the vertical direction.

Referring again to FIG. 2, at 118 the correction value calculated at 110is utilized to align the non-reference images 46 b . . . 46 n to thereference image 150 such that when the reference image 152 is combinedwith the non-reference images 46 b . . . 46 n, a single motioncorrection 2D image of the breast 20 is generated. It should thereforebe realized that a correction value is calculated for each of the 2Dimages 46 b . . . 46 n. In the illustrated embodiment, because there arenine non-reference images 46 b . . . 46 n, at 110 nine correction valuesare calculated, one correction value for each of the non-referenceimages. Optionally, the correction analysis is performed in real time(during the acquisition). If the correction value is above a thresholdvalue (e.g. 0.5 cm or 1 cm) for any of the images, the user is alertedto instruct the patient not to move. The entire imaging procedure mayoptionally repeated, or extended in time to ensure quality, or thecorrection analysis is performed immediately at the end of the imaging(while the patient is in the room). If the correction value is above athreshold value (e.g. 0.5 cm or 1 cm) for any of the images, the user isalerted to repeat the imaging.

Described herein are methods and systems to correct for distortions,such as motion related blurring or artifacts caused as a result ofpatient motion during an MBI scan of a patient's breast. The method andsystems described herein therefore provide improved imaging (bettercontrast, lesion detectability) without adding additional hardware orother costly components to the MBI system. The methods and systemsdescribed herein facilitate reducing patient dosage which may be causedby longer scans that have higher potential of patient motion

It should be noted that the various embodiments may be implemented inhardware, software or a combination thereof. The various embodimentsand/or components, for example, the modules, or components andcontrollers therein, also may be implemented as part of one or morecomputers or processors. The computer or processor may include acomputing device, an input device, a display unit and an interface, forexample, for accessing the Internet. The computer or processor mayinclude a microprocessor. The microprocessor may be connected to acommunication bus. The computer or processor may also include a memory.The memory may include Random Access Memory (RAM) and Read Only Memory(ROM). The computer or processor further may include a storage device,which may be a hard disk drive or a removable storage drive such as asolid state drive, optical disk drive, and the like. The storage devicemay also be other similar means for loading computer programs or otherinstructions into the computer or processor.

As used herein, the term “computer” or “module” may include anyprocessor-based or microprocessor-based system including systems usingmicrocontrollers, reduced instruction set computers (RISC), ASICs, logiccircuits, and any other circuit or processor capable of executing thefunctions described herein. The above examples are exemplary only, andare thus not intended to limit in any way the definition and/or meaningof the term “computer”.

The computer or processor executes a set of instructions that are storedin one or more storage elements, in order to process input data. Thestorage elements may also store data or other information as desired orneeded. The storage element may be in the form of an information sourceor a physical memory element within a processing machine.

The set of instructions may include various commands that instruct thecomputer or processor as a processing machine to perform specificoperations such as the methods and processes of the various embodimentsof the invention. The set of instructions may be in the form of asoftware program. The software may be in various forms such as systemsoftware or application software and which may be embodied as a tangibleand non-transitory computer readable medium. Further, the software maybe in the form of a collection of separate programs or modules, aprogram module within a larger program or a portion of a program module.The software also may include modular programming in the form ofobject-oriented programming. The processing of input data by theprocessing machine may be in response to operator commands, or inresponse to results of previous processing, or in response to a requestmade by another processing machine.

As used herein, the terms “software” and “firmware” are interchangeable,and include any computer program stored in memory for execution by acomputer, including RAM memory, ROM memory, EPROM memory, EEPROM memory,and non-volatile RAM (NVRAM) memory. The above memory types areexemplary only, and are thus not limiting as to the types of memoryusable for storage of a computer program.

It is to be understood that the above description is intended to beillustrative, and not restrictive. For example, the above-describedembodiments (and/or aspects thereof) may be used in combination witheach other. In addition, many modifications may be made to adapt aparticular situation or material to the teachings of the variousembodiments without departing from their scope. While the dimensions andtypes of materials described herein are intended to define theparameters of the various embodiments, they are by no means limiting andare merely exemplary. Many other embodiments will be apparent to thoseof skill in the art upon reviewing the above description. The scope ofthe various embodiments should, therefore, be determined with referenceto the appended claims, along with the full scope of equivalents towhich such claims are entitled. In the appended claims, the terms“including” and “in which” are used as the plain-English equivalents ofthe respective terms “comprising” and “wherein.” Moreover, in thefollowing claims, the terms “first,” “second,” and “third,” etc. areused merely as labels, and are not intended to impose numericalrequirements on their objects. Further, the limitations of the followingclaims are not written in means-plus-function format and are notintended to be interpreted based on 35 U.S.C. §112, sixth paragraph,unless and until such claim limitations expressly use the phrase “meansfor” followed by a statement of function void of further structure.

This written description uses examples to disclose the variousembodiments, including the best mode, and also to enable any personskilled in the art to practice the various embodiments, including makingand using any devices or systems and performing any incorporatedmethods. The patentable scope of the various embodiments is defined bythe claims, and may include other examples that occur to those skilledin the art. Such other examples are intended to be within the scope ofthe claims if the examples have structural elements that do not differfrom the literal language of the claims, or the examples includeequivalent structural elements with insubstantial differences from theliteral languages of the claims.

What is claimed is:
 1. A method for motion correcting molecular breastimaging (MBI) images, said method comprising: obtaining a plurality oftwo-dimensional (2D) images of a breast using a MBI system; selecting areference image from the plurality of 2D images; selecting a feature ofinterest in the reference image; determining a location of the featureof interest in the reference image; calculating a correction value foreach of a plurality of non-reference images based on a difference in thelocation of the feature of interest in the reference image and alocation of the feature of interest in each of the non-reference images;and combining the non-reference images with the reference image based onthe calculated correction values.
 2. The method of claim 1, wherein saidobtaining a plurality of two-dimensional (2D) images of a breast using aMBI system comprises: acquiring data from the MBI system in a list modeformat; and creating a plurality of two-dimensional (2D) images from theacquired data in a list mode format, wherein each one of thetwo-dimensional (2D) images is generated from a sub-set of events in thedata acquired from the MBI system in the list mode format.
 3. The methodof claim 1, wherein selecting a feature of interest comprises selectingat least one of a breast wall or a physical feature within the breast 4.The method of claim 1, wherein calculating the correction valuecomprises: identifying a boundary of the feature of interest in thereference image; identifying a boundary of the feature of interest ineach of the non-reference images; and calculating a shift between theboundary of the feature of interest in the reference image and theboundary of the feature of interest in the non-reference images.
 5. Themethod of claim 1, wherein calculating the correction value comprisescalculating a difference between a location of a boundary of the featureof interest in the reference image and a boundary of the feature ofinterest in the non-reference images.
 6. The method of claim 1, whereincalculating the correction value comprises: identifying a center pointof the feature of interest in the reference image; identifying a centerpoint of the feature of interest in each of the non-reference images;and calculating a shift between the center point of the feature ofinterest in the reference image and the center points of the feature ofinterest in the non-reference images.
 7. The method of claim 1, whereinthe MBI system includes two detectors, said method further comprising:generating a first 2D image using emission data acquired from the firstdetector; generating a second 2D image using emission data acquired fromthe second detector; and combining the first and second 2D images togenerate the reference image.
 8. The method of claim 1, wherein the MBIsystem includes a pair of CZT detectors configured to immobilize thebreast there between.
 9. A molecular breast imaging (MBI) systemcomprising: at least one detector having a plurality of pixels; and aprocessing unit coupled to the detector, the processing unit configuredto obtain a plurality of two-dimensional (2D) images of a breast using aMBI system; receive a user input selecting a reference image from theplurality of 2D images; receive a user input selecting a feature ofinterest in the reference image; determine a location of the feature ofinterest in the reference image; calculate a correction value for eachof a plurality of non-reference images based on a difference in thelocation of the feature of interest in the reference image and alocation of the feature of interest in the non-reference images; andcombine the non-reference images with the reference image based on thecalculated correction values.
 10. The MBI system of claim 9, furthercomprising a pair of CZT detectors configured to immobilize the breastthere between.
 11. The MBI system of claim 9, wherein the processingunit is further configured to: acquire data from the MBI system in alist mode format; and create a plurality of two-dimensional (2D) imagesfrom the acquired data in a list mode format, wherein each one of thetwo-dimensional (2D) images is generated from a sub-set of events in thedata acquired from the MBI system in the list mode format.
 12. The MBIsystem of claim 9, wherein the processing unit is further configured to:identify a boundary of the feature of interest in the reference image;identify a boundary of the feature of interest in each of thenon-reference images; and calculate a shift between the boundary of thefeature of interest in the reference image and the boundaries of thefeature of interest in the non-reference images.
 13. The MBI system ofclaim 9, wherein the processing unit is further configured to calculatea difference between a location of a boundary of the feature of interestin the reference image and a boundary of the feature of interest in thenon-reference images.
 14. The MBI system of claim 9, wherein theprocessing unit is further configured to: receive a user inputidentifying a center point of the feature of interest in the referenceimage; automatically identify a center point of the feature of interestin each of the non-reference images; and calculate a shift between thecenter point of the feature of interest in the reference image and thecenter points of the feature of interest in the non-reference images.15. The MBI system of claim 9, wherein the processing unit is furtherconfigured to: generate a first 2D image using emission data acquiredfrom the first detector; generate a second 2D image using emission dataacquired from the second detector; and combine the first and second 2Dimages to generate the reference image.
 16. A non-transitory computerreadable medium encoded with a program to instruct a processing unit to:obtain a plurality of two-dimensional (2D) images of a breast using aMBI system; receive a user input selecting a reference image from theplurality of 2D images; receive a user input selecting a feature ofinterest in the reference image; determine a location of the feature ofinterest in the reference image; calculate a correction value for eachof a plurality of non-reference images based on a difference in alocation of the feature of interest in the reference image and alocation of the feature of interest in each of the non-reference images;and combine the non-reference images with the reference image based onthe calculated correction values.
 17. The non-transitory computerreadable medium of claim 16, further encoded with a program to instructa processing unit to: acquire data from the MBI system in a list modeformat; and create a plurality of two-dimensional (2D) images from theacquired data in a list mode format, wherein each one of thetwo-dimensional (2D) images is generated from a sub-set of events in thedata acquired from the MBI system in the list mode format.
 18. Thenon-transitory computer readable medium of claim 16, further encodedwith a program to instruct a processing unit to: identify a boundary ofthe feature of interest in the reference image; identify a boundary ofthe feature of interest in each of the non-reference images; andcalculate a shift between the boundary of the feature of interest in thereference image and the boundaries of the feature of interest in thenon-reference images.
 19. The non-transitory computer readable medium ofclaim 16, further encoded with a program to instruct a processing unitto calculate a difference between a location of a boundary of thefeature of interest in the reference image and a boundary of the featureof interest in the non-reference images.
 20. The non-transitory computerreadable medium of claim 16, further encoded with a program to instructa processing unit to: receive a user input identifying a center point ofthe feature of interest in the reference image; automatically identify acenter point of the feature of interest in each of the non-referenceimages; and calculate a shift between the center point of the feature ofinterest in the reference image and the center points of the feature ofinterest in the non-reference images.